Skip to Main content Skip to Navigation
Theses

Scheduling of power system cells integrating stochastic power sources

Abstract : Energy supply and climate change are nowadays two of the most outstanding problems which societies have to cope with under a context of increasing energy needs. Public awareness of these problems is driving political willingness to take actions for tackling them in a swift and efficient manner. Such actions mainly focus in increasing energy efficiency, in decreasing dependence on fossil fuels, and in reducing greenhouse gas emissions. In this context, power systems are undergoing important changes in the way they are planned and managed. On the one hand, vertically integrated structures are being replaced by market structures in which power systems are unbundled. On the other, power systems that once relied on large power generation facilities are witnessing the end of these facilities' life-cycle and, consequently, their decommissioning. The role of distributed energy resources such as wind and solar power generators is becoming increasingly important in this context. However, the large-scale integration of such type of generation presents many challenges due, for instance, to the uncertainty associated to the variability of their production. Nevertheless, advanced forecasting tools may be combined with more controllable elements such as energy storage devices, gas turbines, and controllable loads to form systems that aim to reduce the impacts that may be caused by these uncertainties. This thesis addresses the management under market conditions of these types of systems that act like independent societies and which are herewith named power system cells. From the available literature, a unified view of power system scheduling problems is also proposed as a first step for managing sets of power system cells in a multi-cell management framework. Then, methodologies for performing the optimal day-ahead scheduling of single power system cells are proposed, discussed and evaluated under both a deterministic and a stochastic framework that directly integrates the uncertainty information into the scheduling process. Results show that the utilization of the proposed approaches may lead to important advantages for operators managing these types of power system cells.
Document type :
Theses
Complete list of metadatas

Cited literature [138 references]  Display  Hide  Download

https://pastel.archives-ouvertes.fr/tel-00409587
Contributor : Magalie Prudon <>
Submitted on : Thursday, August 13, 2009 - 9:34:34 AM
Last modification on : Thursday, September 24, 2020 - 5:22:02 PM
Long-term archiving on: : Tuesday, June 15, 2010 - 10:23:45 PM

Identifiers

  • HAL Id : tel-00409587, version 1

Citation

Luis Costa. Scheduling of power system cells integrating stochastic power sources. Electric power. École Nationale Supérieure des Mines de Paris, 2008. English. ⟨NNT : 2008ENMP1631⟩. ⟨tel-00409587⟩

Share

Metrics

Record views

1411

Files downloads

1950